BACKGROUND: This study aims to establish whether health reporting differs by education level and, if so, to determine the extent to which this biases the measurement of health inequalities among older Europeans. METHODS: Data are from the Survey of Health, Ageing and Retirement in Europe (SHARE) covering eight countries. Differential reporting of health by education is identified from ratings of anchoring vignettes that describe fixed health states. Ratings of own health in six domains (mobility, pain, sleep, breathing, emotional health and cognition) are corrected for differences in reporting using an extended ordered probit model. For each country and health domain, we compare the corrected with the uncorrected age-sex standardized high-to-low education rate ratio for the absence of a health problem. RESULTS: Before correction for reporting differences across the 48 combinations of country by health domain, there was no inequality in health by education (P > 0.05) in 32 of 48 cases. However, there were reporting differences by education (P < 0.05) in 29 out of 48 cases. In general, higher educated older Europeans are more likely to rate a given health state negatively (except for Spain and Sweden). Correcting for these differences generally increases health inequalities (except for Spain and Sweden) and results in the emergence of inequalities in 18 cases (P < 0.05), which may be considered 'statistically significant'. The greatest impact is in Belgium, Germany and The Netherlands, where inequalities (P < 0.05) appear only after adjustment in four of the six health domains. CONCLUSIONS: These results emphasize the need to account for differences in the reporting of health. Measured health inequalities by education are often underestimated, and even go undetected, if no account is taken of these reporting differences.
BACKGROUND: This study aims to establish whether health reporting differs by education level and, if so, to determine the extent to which this biases the measurement of health inequalities among older Europeans. METHODS: Data are from the Survey of Health, Ageing and Retirement in Europe (SHARE) covering eight countries. Differential reporting of health by education is identified from ratings of anchoring vignettes that describe fixed health states. Ratings of own health in six domains (mobility, pain, sleep, breathing, emotional health and cognition) are corrected for differences in reporting using an extended ordered probit model. For each country and health domain, we compare the corrected with the uncorrected age-sex standardized high-to-low education rate ratio for the absence of a health problem. RESULTS: Before correction for reporting differences across the 48 combinations of country by health domain, there was no inequality in health by education (P > 0.05) in 32 of 48 cases. However, there were reporting differences by education (P < 0.05) in 29 out of 48 cases. In general, higher educated older Europeans are more likely to rate a given health state negatively (except for Spain and Sweden). Correcting for these differences generally increases health inequalities (except for Spain and Sweden) and results in the emergence of inequalities in 18 cases (P < 0.05), which may be considered 'statistically significant'. The greatest impact is in Belgium, Germany and The Netherlands, where inequalities (P < 0.05) appear only after adjustment in four of the six health domains. CONCLUSIONS: These results emphasize the need to account for differences in the reporting of health. Measured health inequalities by education are often underestimated, and even go undetected, if no account is taken of these reporting differences.
Authors: E van Doorslaer; A Wagstaff; H van der Burg; T Christiansen; D De Graeve; I Duchesne; U G Gerdtham; M Gerfin; J Geurts; L Gross; U Häkkinen; J John; J Klavus; R E Leu; B Nolan; O O'Donnell; C Propper; F Puffer; M Schellhorn; G Sundberg; O Winkelhake Journal: J Health Econ Date: 2000-09 Impact factor: 3.883
Authors: Archana Singh-Manoux; Aline Dugravot; Martin J Shipley; Jane E Ferrie; Pekka Martikainen; Marcel Goldberg; Marie Zins Journal: Int J Epidemiol Date: 2007-11-19 Impact factor: 7.196
Authors: Teresa Bago d'Uva; Maarten Lindeboom; Owen O'Donnell; Eddy van Doorslaer Journal: J R Stat Soc Ser A Stat Soc Date: 2011-07 Impact factor: 2.483